This Project Grant award for $175,000 was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The project, titled "Formalizing Human-Interpretable Machine Learning," aims to develop approaches for training artificial intelligence systems, such as self-driving cars, to make their decision-making processes more transparent and interpretable to people. The research will involve pairing...
This Project Grant award, valued at $150,000.00, was granted by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The primary awardee, the University of North Carolina at Chapel Hill (UNC-CH), will develop a new approach called Algorithm-Informed Neural Networks (AINNs) that integrates well-established algorithmic principles into the design of neural networks. This approach aims to enhance the explainability, reliability,...
The National Science Foundation (NSF) awarded a $582,031 Project Grant under the Computer and Information Science and Engineering program (CFDA 47.070) to the Regents of the University of Michigan, doing business as the University of Michigan. The grant will fund a 5-year research project focused on "Achieving Explainable Artificial Intelligence (AI) Through Human-AI Interaction." The goal of the project is to develop new scientific knowledge and design guidelines for delivering...
This $300,000 EAGER (Early-concept Grants for Exploratory Research) award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program aims to develop a framework called XAISE (eXplainable Artificial Intelligence for Science and Engineering) to enhance the explainability of artificial intelligence (AI) models for scientific and engineering applications. The project seeks to design, develop, and implement XAISE to improve the explainability of...
The National Science Foundation (NSF) awarded a $329,183 Project Grant to the College of William & Mary under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant, awarded on October 1, 2023, will fund the development of a framework and methodology to enable researchers and software engineers to better interpret the behavior of AI-powered developer tools that leverage neural language models for source code. The project aims to generate global and local...
This $348,227 federal Project Grant award, made by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, focuses on improving the scalability and effectiveness of using large language models (LLMs) in healthcare applications. The key objectives are to develop an evaluation framework to address issues like factual and faithfulness hallucinations in LLM outputs, and to introduce innovative reinforcement learning methods to align LLM...
This $240,000 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The award supports the development of a new class of computational frameworks that combine large language models with neural operator learning techniques to address key challenges in modeling spatiotemporal phenomena in biomedical research. The research aims to transform biological and medical studies by adapting...
This Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $150,000 to fund the development of Algorithm-Informed Neural Networks (AINNs). AINNs integrate well-established algorithmic principles into neural network architectures to enhance the explainability, reliability, and efficiency of AI systems. The key research tasks include designing AINN models that leverage predefined logical rules to reduce...
This $139,660 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant supports research at the College of William and Mary to develop novel online data mining algorithms that can provide transparent and interpretable machine learning models for real-time applications such as crowd movement prediction, disaster monitoring, and pandemic response. Key objectives include: 1)...
This National Science Foundation (NSF) Project Grant, awarded under the Computer and Information Science and Engineering program (CFDA 47.070), provides $220,000 to Yale University from September 1, 2023 through August 31, 2027. The project aims to develop a smarter artificial intelligence (AI) system to better understand and analyze complex medical images, such as those from multiple scans of a patient. The research team will tackle challenges to make the AI system more scalable, interpretable,...